We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Can a recent BBF algorithm be added to the library- https://github.com/google-research/google-research/tree/master/bigger_better_faster?
It is model free single agent RL algorithm which this library specializes in. It`s more sample-efficient then Dreamerv3 or PPO at least in some task
Addition of BBF algorithm to the library so everyone can use it for custom environments
Add other algorithm with comparable efficiency
paper - https://paperswithcode.com/paper/bigger-better-faster-human-level-atari-with
The text was updated successfully, but these errors were encountered:
Hello, That would indeed be a good addition for SB3 contrib, would you be willing to contribute?
Sorry, something went wrong.
I have a knowledge of RL on the level of running stable baselines 3 on custom envs. So I`m willing but not able to do it.
Can contribute only by testing for now
No branches or pull requests
🚀 Feature
Can a recent BBF algorithm be added to the library- https://github.com/google-research/google-research/tree/master/bigger_better_faster?
Motivation
It is model free single agent RL algorithm which this library specializes in. It`s more sample-efficient then Dreamerv3 or PPO at least in some task
Pitch
Addition of BBF algorithm to the library so everyone can use it for custom environments
Alternatives
Add other algorithm with comparable efficiency
Additional context
paper - https://paperswithcode.com/paper/bigger-better-faster-human-level-atari-with
Checklist
The text was updated successfully, but these errors were encountered: